Unveiling Britain’s Subsurface with 3D Magnetotellurics
Researchers have produced the first comprehensive 3D electrical resistivity model of Britain, offering a new view into the country’s hidden geophysical structures. The model, called BERM-2024, is built from long-period magnetotelluric (MT) data that track variations in electric and magnetic fields at Earth’s surface. By interpreting how easily electrical currents travel through rocks, the team can infer the resistivity of the crust and upper mantle, revealing the fingerprints of tectonic features, magmatic intrusions, and sedimentary basins.
Magnetotelluric surveys are particularly powerful because resistivity responds to a range of rock properties, including mineral composition, fluid content, and temperature. In Britain, where complex tectonics have shaped the landscape over hundreds of millions of years, MT data can complement seismic and gravity studies, helping scientists draw a more complete picture of the subsurface. The researchers also emphasize an important, practical aspect: resistivity models can illuminate how space weather affects human infrastructure by informing forecasts of geoelectric fields that drive geomagnetically induced currents.
Building the BERM-2024 Model
The study integrates MT measurements from 69 sites across Great Britain, combining fresh data with legacy records to achieve broad geographic coverage. The long-period data—collected with observations lasting four to six weeks at a time—provide sensitivity to deep structures, enabling the team to resolve features down to about 200 kilometers (125 miles) below the surface. Creating the model involved meticulous processing to correct time-series data and to account for coastal effects caused by seawater conductivity, which can bias inversions near shorelines.
The resulting 3D resistivity model not only confirms known tectonic elements but also highlights new anomalies that warrant further investigation. Among the notable findings are highly conductive zones beneath Scotland’s Southern Uplands Terrane, a resistive anomaly beneath Anglesey, and a strikingly conductive body in the West Midlands region at depths between 85 and 140 kilometers (52–87 miles). These features may point to variations in rock type, fluid pathways, or past magmatic activity that escape detection by surface observations alone.
Implications for Geoscience and Space Weather
Beyond enriching our understanding of Britain’s geological history, the BERM-2024 model demonstrates the practical value of MT surveys in modern geoscience. By correlating electrical resistivity with subsurface structures, researchers can refine models of crustal architecture, map intrusions and basins, and interpret regional geodynamic processes with greater confidence.
Crucially, the team explored how this resistivity framework can inform space weather preparedness. They tested the model’s ability to estimate the surface electric field during a solar storm that occurred on 10–11 October 2024, a period marked by bright auroras across the Northern Hemisphere. The modeled electric-field time series showed strong agreement with direct measurements at observatories, validating MT-based approaches as useful tools for forecasting geomagnetically induced currents. As vital infrastructure—from power grids to communications networks—faces increasing exposure to space weather, such modeling approaches provide a path toward more resilient planning and response strategies.
Looking Ahead
BERM-2024 marks a milestone in British geophysics by delivering a highly resolved, three-dimensional view of the island’s beneath-the-surface structure. The model’s depth reach and newly revealed anomalies offer a roadmap for future investigations, including targeted geophysical surveys and integrative studies that combine MT data with seismic, gravity, and petrological analyses. As researchers continue to refine resistivity methods and expand MT networks, Britain stands to gain a clearer understanding of its subsurface, with benefits spanning natural hazard assessment, resource evaluation, and space weather forecasting.
